A Fitts’ Law Study of Gaze-Hand Alignment for Selection in 3D User Interfaces 

Uta Wagner, Mathias N. Lystbæk, Pavel Manakhov, Jens Emil Grønbæk, Ken Pfeufer, and Hans Gellersen

CHI '23: CHI Conference on Human Factors in Computing Systems

Gaze-Hand Alignment has recently been proposed for multimodal selection in 3D. The technique takes advantage of gaze for target pre-selection, as it naturally precedes manual input. Selection is then completed when manual input aligns with gaze on the target, without need for an additional click method. In this work we evaluate two alignment techniques, Gaze&Finger and Gaze&Handray, combining gaze with image plane pointing versus raycasting, in comparison with hands-only baselines and Gaze&Pinch as established multimodal technique. We used Fitts’ Law study design with targets presented at different depths in the visual scene, to assess effect of parallax on performance. The alignment techniques outperformed their respective hands-only baselines. Gaze&Finger is efficient when targets are close to the image plane but less performant with increasing target depth due to parallax. 

Uta Wagner, Mathias N. Lystbæk, Pavel Manakhov, Jens Emil Grønbæk, Ken Pfeufer, and Hans Gellersen. 2023. A Fitts’ Law Study of Gaze-Hand Alignment for Selection in 3D User Interfaces. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23), April 23–28, 2023, Hamburg, Germany. ACM, New York, NY, USA, 15 pages

 

BibTex

@inproceedings{10.1145/3544548.3581423, 
	author={Uta Wagner and Mathias N. Lystbæk and Pavel Manakhov and Jens Emil Grønbæk and Ken Pfeuffer and Hans Gellersen}, 
	title={A Fitts’ Law Study of Gaze-Hand Alignment for Selection in 3D User Interfaces},  
	year = {2023}, 
	publisher = {Association for Computing Machinery}, 
	address = {New York, NY, USA}, 
	booktitle = {Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems}, 
	location = {Hamburg, Germany}, 
	series = {CHI '23}, 
	numpages = {15},
	doi = {10.1145/3544548.3581423}, 
	url = {https://doi.org/10.1145/3544548.3581423}, 
	address = {New York, NY, USA}
}